【论文学习】Path Aggregation Network for Instance Segmentation

主要记录Fully-connected Fusion

Motivation Fully-connected layers, or MLP, were widely used in mask prediction in instance segmentation [10, 41,34] and mask proposal generation [48, 49]. Results of [8, 33] show that FCN is also competent in predicting pixelwise masks for instances. Recently, Mask R-CNN [21] applied a tiny FCN on the pooled feature grid to predict corresponding masks avoiding competition between classes.
We note fc layers yield different properties compared with FCN where the latter gives prediction at each pixel based on a local receptive field and parameters are shared at different spatial locations. Contrarily, fc layers are location sensitive since predictions at different spatial locations are achieved by varying sets of parameters. So they have the ability to adapt to different spatial locations. Also prediction at each spatial location is made with global information of the entire proposal. It is helpfu